A framework for healthcare support in the rural and low income areas of the developing world

Cyber-Healthcare is an emerging field of the healthcare domain that builds upon cyber physical health systems (CPHSs) to provide pervasive access to medical services any time and from anywhere in the world where medical expertise is available. It is expected to change the way healthcare is delivered in the developing world and enable both its rural and urban settings to leapfrog from poorly equipped to medically prepared environments capable of tackling some of its most challenging health issues. However, owing to their infancy stage in the developing world, CPHSs require substantial research and practical work to move from their theoretical boundaries into the development, deployment and exploitation phase. This paper proposes a Cyber-Healthcare framework and its implementation as a fog-based CPHS infrastructure using low-cost lightweight devices to achieve patients' condition recognition as a first step towards the implementation of digital healthcare support systems in the developing world. We propose a multi-layer architecture for the framework and consider a patients' condition recognition system that uses machine learning techniques as a key component of the framework. We present experimental results that reveal i) the relative efficiency of different machine learning algorithms used for patient condition recognition and ii) the storage and processing overheads incurred by two popular lightweight embedded devices when used as fog computing devices in the CPHS.